coefficients for GLM

[Trevor Parker <trevor.parker@tfrc.csiro.au>]

Hello S-plus enthusiasts,
 
I have run a GLM using 2 degree poynomials as independents. The model looks like this:

forest.object <- glm(forest ~ poly(slope,2) + poly(aspectns,2), family=binomial(logit), data="">

When I use the coefficients from forest.object to predict forest I get erroneous results. i.e very small values


The predictive GLM form I am using is:


log(p/1-p) = intercept + coef1*slope + coef2*sqr(slope) + coef3*aspectns + coef4*sqr(aspectns)


where intercept and coef1 to 4 are from forest.object.


When I run the model:


forest.object <- glm(forest ~ slope + aspectns, family=binomial(logit), data="">

and use the coefficents to predict forest i.e log(p/1-p) = intercept + coef1*slope + coef2*aspectns


it works well.




I have tried using poly.transform but it appears to only work for models with one independent variable.


Am I using the polynomial form correctly. Your help would be appreciated.




Regards


 
Trevor Parker
GIS Technician / Spatial Analyst
CSIRO - Tropical Forest Research Centre
P.O Box 780
Atherton QLD
Australia 4883
Ph: ++ 61 (0) 7 4091 8800
Fax: ++ 61 (0) 7 4091 8888